Abstract 2808: cfDNA multi-omics profiling and tissue of origin predictions in cancers of unknown primary
Authors: Alicia-Marie Conway, Alexandra Clipson, Francesca Chemi, Simon Pearce, Katarzyna Kamieniecka, Saba Ferdous, Sophie Richardson, Elaine Kilgour, Matthew G. Krebs, Alastair Kerr, Dominic Rothwell, Natalie Cook, Caroline Dive
Journal: Cancer Research (2022)

Abstract Cancers of Unknown Primary (CUP) comprise a heterogeneous group of metastatic cancers where the primary site is undetectable. It accounts for 2% of all new UK cancer diagnoses and is the 6th leading cause of cancer death. Favourable subsets of CUP exist, based on clinico-pathological features, and although these patients have improved clinical outcomes, they make up only 20% of patients with CUP. The evolution of molecular profiling and tissue-of-origin (TOO) classifiers has the potential to transform diagnosis and management of patients with CUP. Reliable molecular profiling requires good quality and quantity tumour tissue material, often scarce in patients with CUP. Liquid biopsies offer an alternative, minimally invasive approach. We developed a novel cell-free DNA (cfDNA)-based multi-omics assay combining methylation profiling with mutation and copy number alterations (CNA) detection, to enable TOO prediction and biomarker discovery to aid treatment stratification. Methods: Two novel library preparation methods were applied to 41 CUP cfDNA samples, 80 non-cancer controls and 80 cfDNA samples from known tumour types (breast, lung, colorectal cancer): 1) Targeted (641 gene panel) next generation sequencing (NGS); 2) A multiplex genome-wide methylation capture assay (T7-MBDSeq). Both sequencing outputs can estimate CNA. Cancer Genome Interpreter (CGI) was used to evaluate the potential actionability of molecular alterations detected. A novel TOO classifier, generated utilising in silico dilution mixture sets derived from The Cancer Genome Atlas (TCGA) methylation data, demonstrated an AUROC of 0.96 across 15 different cancer groups. This was applied to cfDNA methylation data from known tumour types to test performance accuracy and subsequently applied to CUP cfDNA samples. Results: Multi-omics profiling from cfDNA was completed for 34/41 patients with CUP. cfDNA mutation profiling and estimated CNA analysis so far revealed &amp;gt;350 alterations across 225 genes. 17/34 (50%) of patients harboured potentially actionable alterations by CGI and, where performed, 68% of tumour mutations were concordant in the cfDNA. cfDNA methylation profiling revealed tumour-specific methylation changes in breast, lung and colorectal cancers. Our preliminary TOO classifier performance in these tumour types had an overall sensitivity and specificity of 85% and 98%, respectively. In patients with CUP, a predicted TOO was made in 26/41 (63%) patients and for 6 patients, where a subsequent primary tumour diagnosis was made, the TOO prediction was correct. Conclusions: cfDNA multi-omics profiling revealed potential therapeutic benefit in 77% of this retrospective CUP cohort and illustrates the potential to re-classify patients to primary tumour types where alternative therapies may improve clinical outcomes. Further multi-omics cfDNA profiling of the CUP cohort and validation in known primary cancer types are ongoing. Citation Format: Alicia-Marie Conway, Alexandra Clipson, Francesca Chemi, Simon Pearce, Katarzyna Kamieniecka, Saba Ferdous, Sophie Richardson, Elaine Kilgour, Matthew G. Krebs, Alastair Kerr, Dominic Rothwell, Natalie Cook, Caroline Dive. cfDNA multi-omics profiling and tissue of origin predictions in cancers of unknown primary [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2808.